An increasing number of data-intensive distributed applications are being developed to serve various needs, such as processing very large data sets that generally cannot be handled by a single computer. Instead, clusters of computers are employed to distribute various tasks, such as organizing and accessing the data and performing related operations with respect to the data. Various applications and frameworks have been developed to interact with such large data sets, including Hive, HBase, Hadoop, Spark, among others.
At the same time, virtualization techniques have gained popularity and are now commonplace in data centers and other computing environments in which it is useful to increase the efficiency with which computing resources are used. In a virtualized environment, one or more virtual nodes are instantiated on an underlying physical computer and share the resources of the underlying computer. Accordingly, rather than implementing a single node per host computing system, multiple nodes may be deployed on a host to more efficiently use the processing resources of the computing system. These virtual nodes may include full operating system virtual machines, Linux containers, such as Docker containers, jails, or other similar types of virtual containment nodes.
In addition to the large-scale processing clusters that provide operations on the data, some computing environments may employ visualization and monitoring applications, or edge services, to more effectively render and interact with the operations of the processing cluster. These edge services, which may comprise Splunk, Hunk, Graylog, Platfora, or some other visualization and monitoring service, communicate with the large-scale processing framework nodes within the cluster and provide feedback to administrators and users associated with the cluster. However, although the edge services provide valuable information to the users and administrators associated with the large-scale processing clusters, it is often difficult and cumbersome to generate the necessary configuration information that permits the edge services to communicate with the large-scale processing cluster.